Module organiser: Dr Nicholas Vasilakos
The module is designed for MBA-level students who wish to have a working knowledge of some popular econometric techniques with forecasting applications. Particular emphasis will be given to techniques and procedures that (1) enable analysts to come up with reliable forecasts; and (2) performance tests that can be applied to assess the quality of the methods applied and compare alternative methodologies. The module will focus primarily on issues related with the analysis of time-series data, although other data formats (and related methodologies) will be briefly discussed.
This is a quantitative, mathematical module: although it has been designed to focus on the practical aspects of forecasting, it is still econometrics.
By the end of the module, students should be able to:
- Have a working knowledge of core forecasting-related topics on intermediate-level econometric theory
- Apply and compare a number of forecasting techniques
- Develop their data handling skills, using specialised software
- Have a solid understanding of how to interpret and report their results
- Read, understand and interpret computerised econometric output
- Apply and interpret a range of diagnostic tests.
Essentially the core skill that students will develop with this module, is the ability to apply some popular forecasting techniques, in order to obtain estimates for the future performance of economic variables of interest (e.g. future sales, demand etc.). In the process, they will also have to improve substantially their data handling skills, using appropriate software.
Please note: This information is subject to review and change without notice.